Spin-torque building blocks

Guanine-based spin valve with spin rectification effect for an artificial memory element

Non-volatile electronic memory elements are very attractive for applications, not only for information storage but also in logic circuits, sensing devices and neuromorphic computing. Here, a ferroelectric film of guanine nucleobase is used in a resistive memory junction sandwiched between two different ferromagnetic films of Co and CoCr alloys. The magnetic films have an in-plane easy axis of magnetization and different coercive fields whereas the guanine film ensures a very long spin transport length, at 100 K. The non-volatile resistance states of the multiferroic spintronic junction with two-terminals are manipulated by a combined action of small external magnetic and electric fields. Thus, the magnetic field controls the relative orientation of the magnetization of the metallic ferromagnetic electrodes, that leads to different magnetoresistance states. The orientation and the magnitude of the electric field controls the orientation of the polarization of the guanine ferroelectric barrier, that leads to different electroresistance states, respectively. Moreover, we have observed a strong interfacial coupling of the two parameters. Consequently, positive and negative magnetoresistance hysteresis loops corresponding to spin rectification effects and non-hysteretic (erased) resistive states are manipulated with the electric field by switching the orientation of the electrical polarization of the organic ferroelectric.

Antiferromagnetic spin-torque diode effect in a kagome Weyl semimetal

Spintronics based on ferromagnets has enabled the development of microwave oscillators and diodes. To achieve even faster operation, antiferromagnets hold great promise despite their challenging manipulation. So far, controlling antiferromagnetic order with microwave currents remains elusive. Here we induce the coherent rotation of antiferromagnetic spins in a Weyl antiferromagnet W/Mn3Sn epitaxial bilayer by DC spin-orbit torque. We show the efficient coupling of this spin rotation with microwave current. The coupled dynamics produce a DC anomalous Hall voltage through rectification, which we coin the antiferromagnetic spin-torque diode effect. Unlike in ferromagnetic systems, the output voltage shows minimal dependence on frequency because of the stabilization of the precession cone angle by exchange interactions. Between 10 GHz and 30 GHz, the output voltage decreases by only 10%. Numerical simulations further reveal that the rectification signals arise from the fast frequency modulation of chiral spin rotation by microwave spin-orbit torque. These results may help the development of high-speed microwave devices for next-generation telecommunication applications.

Multimodal Locomotion and Dynamic Interaction of Hydrogel Microdisks at the Air-Water Interface under Magnetic and Light Stimuli

The potential applications of hydrogel microrobots in biomedicine and environmental exploration have sparked significant interest in understanding their behavior under multiphysical fields. This study explores the multimodal locomotion and dynamic interaction of hydrogel microrobots at the air-water interface under magnetic and light stimuli. A pair of hydrogel microrobots at the air-water interface exhibits a transition from cooperative, combined rotation to interactive behavior, involving both rotation and revolution under the influence of a rotating magnetic field (RMF), and a shift from attraction to separation under near-infrared (NIR) light, demonstrating the dynamic modulation of their behaviors in response to different stimuli. Notably, the behavioral patterns of multiple hydrogel microrobots under multiphysical fields indicate that NIR light can enhance interactive motion behaviors under RMFs and extend the range of motion trajectories. Dynamic models for each condition are established and analyzed based on dynamic equilibrium, and their behavior can be modulated by parameters such as magnetic particle concentration, magnetic field frequency, and NIR light intensity. This work introduces a novel strategy for regulating and controlling the dynamic behaviors of hydrogel microrobots, offering new insights into their multiphysical field locomotion.

Integrated Artificial Neural Network with Trainable Activation Function Enabled by Topological Insulator-Based Spin-Orbit Torque Devices

Nonvolatile memristors offer a salient platform for artificial neural network (ANN), yet the integration of different function and algorithm blocks into one hardware system remains challenging. Here we demonstrate the brain-like synaptic (SOT-S) and neuronal (SOT-N) functions in the Bi2Te3/CrTe2 heterostructure-based spin-orbit torque (SOT) device. The SOT-S unit exhibits highly linear and symmetrical long-term potentiation/depression process, resulting in a fast-training of the MNIST data set with the classification accuracy above 90%. Meanwhile, the Sigmoid-shape transition curve inherited in the SOT-N cell replaces the software-based activation function block, hence reducing the system complexity. On this basis, we employ a serial-connected, voltage-mode sensing ANN architecture to enhance the vector-matrix multiplication signal strength with low reading error of 0.61% while simplifying the peripheral circuitry. Furthermore, the trainable activation function of SOT-N enables the implementation of the Batch Normalization algorithm and activation operation within one clock cycle, which bring about improved on/off-chip training performance close to the ideal baseline.

First-Principles Simulation and Materials Screening for Spin-Orbit Torque in 2D van der Waals Heterostructures

Recent advancements in spin-orbit torque (SOT) technology in two-dimensional van der Waals (2D vdW) materials have not only pushed spintronic devices to their atomic limits but have also unveiled unconventional torques and novel spin-switching mechanisms. The vast diversity of SOT observed in numerous 2D vdW materials necessitates a screening strategy to identify optimal materials for torque device performance. However, such a strategy has yet to be established. To address this critical issue, a combination of density functional theory and non-equilibrium Green's function is employed to calculate the SOT in various 2D vdW bilayer heterostructures. This leads to the discovery of three high SOT systems: WTe2/CrSe2, MoTe2/VS2, and NbSe2/CrSe2. Furthermore, a figure of merit that allows for rapid and efficient estimation of SOT is proposed, enabling high-throughput screening of optimal materials and devices for SOT applications in the future.

Unravelling the operation of organic artificial neurons for neuromorphic bioelectronics

Organic artificial neurons operating in liquid environments are crucial components in neuromorphic bioelectronics. However, the current understanding of these neurons is limited, hindering their rational design and development for realistic neuronal emulation in biological settings. Here we combine experiments, numerical non-linear simulations, and analytical tools to unravel the operation of organic artificial neurons. This comprehensive approach elucidates a broad spectrum of biorealistic behaviors, including firing properties, excitability, wetware operation, and biohybrid integration. The non-linear simulations are grounded in a physics-based framework, accounting for ion type and ion concentration in the electrolytic medium, organic mixed ionic-electronic parameters, and biomembrane features. The derived analytical expressions link the neurons spiking features with material and physical parameters, bridging closer the domains of artificial neurons and neuroscience. This work provides streamlined and transferable guidelines for the design, development, engineering, and optimization of organic artificial neurons, advancing next generation neuronal networks, neuromorphic electronics, and bioelectronics.

Electrically Induced Angular Momentum Flow between Separated Ferromagnets

Converting angular momentum between different degrees of freedom within a magnetic material results from a dynamic interplay between electrons, magnons, and phonons. This interplay is pivotal to implementing spintronic device concepts that rely on spin angular momentum transport. We establish a new concept for long-range angular momentum transport that further allows us to address and isolate the magnonic contribution to angular momentum transport in a nanostructured metallic ferromagnet. To this end, we electrically excite and detect spin transport between two parallel and electrically insulated ferromagnetic metal strips on top of a diamagnetic substrate. Charge-to-spin current conversion within the ferromagnetic strip generates electronic spin angular momentum that is transferred to magnons via electron-magnon coupling. We observe a finite angular momentum flow to the second ferromagnetic strip across a diamagnetic substrate over micron distances, which is electrically detected in the second strip by the inverse charge-to-spin current conversion process. We discuss phononic and dipolar interactions as the likely cause to transfer angular momentum between the two strips. Moreover, our Letter provides the experimental basis to separate the electronic and magnonic spin transport and thereby paves the way towards magnonic device concepts that do not rely on magnetic insulators.

Non-hermiticity in spintronics: oscillation death in coupled spintronic nano-oscillators through emerging exceptional points

The emergence of exceptional points (EPs) in the parameter space of a non-hermitian (2D) eigenvalue problem has long been interest in mathematical physics, however, only in the last decade entered the scope of experiments. In coupled systems, EPs give rise to unique physical phenomena, and enable the development of highly sensitive sensors. Here, we demonstrate at room temperature the emergence of EPs in coupled spintronic nanoscale oscillators and exploit the system's non-hermiticity. We observe amplitude death of self-oscillations and other complex dynamics, and develop a linearized non-hermitian model of the coupled spintronic system, which describes the main experimental features. The room temperature operation, and CMOS compatibility of our spintronic nanoscale oscillators means that they are ready to be employed in a variety of applications, such as field, current or rotation sensors, radiofrequeny and wireless devices, and in dedicated neuromorphic computing hardware. Furthermore, their unique and versatile properties, notably their large nonlinear behavior, open up unprecedented perspectives in experiments as well as in theory on the physics of exceptional points expanding to strongly nonlinear systems.

Exploration of field-like torque and field-angle tunability in coupled spin-torque nano oscillators for synchronization

We investigate the influence of field-like torque and the direction of the external magnetic field on a one-dimensional array of serially connected spin-torque nano oscillators (STNOs), having free layers with perpendicular anisotropy, to achieve complete synchronization between them by analyzing the associated Landau-Lifshitz-Gilbert-Slonczewski equation. The obtained results for synchronization are discussed for the cases of 2, 10, and 100 oscillators separately. The roles of the field-like torque and the direction of the external field on the synchronization of the STNOs are explored through the Kuramoto order parameter. While the field-like torque alone is sufficient to bring out global synchronization in the system made up of a small number of STNOs, the direction of the external field is also needed to be slightly tuned to synchronize the one-dimensional array of a large number of STNOs. The formation of complete synchronization through the construction of clusters within the system is identified for the 100 oscillators. The large amplitude synchronized oscillations are obtained for small to large numbers of oscillators. Moreover, the tunability in frequency for a wide range of currents is shown for the synchronized oscillations up to 100 spin-torque oscillators. In addition to achieving synchronization, the field-like torque increases the frequency of the synchronized oscillations. The transverse Lyapunov exponents are deduced to confirm the stable synchronization in coupled STNOs due to the field-like torque and to validate the results obtained in the numerical simulations. The output power of the array is estimated to be enhanced substantially due to complete synchronization by the combined effect of field-like torque and tunability of the field-angle.

Room-Temperature van der Waals Ferromagnet Switching by Spin-Orbit Torques

The emerging wide varieties of the van der Waals (vdW) magnets with atomically thin and smooth interfaces hold great promise for next-generation spintronic devices. However, due to the lower Curie temperature of the vdW ferromagnets than room temperature, electrically manipulating its magnetization at room temperature has not been realized. In this work, it is demonstrated that the perpendicular magnetization of the vdW ferromagnet Fe3 GaTe2 can be effectively switched at room temperature in the Fe3 GaTe2 /Pt bilayer by spin-orbit torques (SOTs) with a relatively low current density of 1.3 × 107 A cm-2 . Moreover, the high SOT efficiency of ξDL ≈ 0.28 is quantitatively determined by harmonic measurements, which is higher than those in Pt-based heavy metal/conventional ferromagnet devices. The findings of room-temperature vdW ferromagnet switching by SOTs provide a significant basis for the development of vdW-ferromagnet-based spintronic applications.

Emerging memristive artificial neuron and synapse devices for the neuromorphic electronics era

Growth of data eases the way to access the world but requires increasing amounts of energy to store and process. Neuromorphic electronics has emerged in the last decade, inspired by biological neurons and synapses, with in-memory computing ability, extenuating the 'von Neumann bottleneck' between the memory and processor and offering a promising solution to reduce the efforts both in data storage and processing, thanks to their multi-bit non-volatility, biology-emulated characteristics, and silicon compatibility. This work reviews the recent advances in emerging memristive devices for artificial neuron and synapse applications, including memory and data-processing ability: the physics and characteristics are discussed first, i.e., valence changing, electrochemical metallization, phase changing, interfaced-controlling, charge-trapping, ferroelectric tunnelling, and spin-transfer torquing. Next, we propose a universal benchmark for the artificial synapse and neuron devices on spiking energy consumption, standby power consumption, and spike timing. Based on the benchmark, we address the challenges, suggest the guidelines for intra-device and inter-device design, and provide an outlook for the neuromorphic applications of resistive switching-based artificial neuron and synapse devices.

Associative memory by virtual oscillator network based on single spin-torque oscillator

A coupled oscillator network may be able to perform an energy-efficient associative memory operation. However, its realization has been difficult because inhomogeneities unavoidably arise among the oscillators during fabrication and lead to an unreliable operation. This issue could be resolved if the oscillator network were able to be formed from a single oscillator. Here, we performed numerical simulations and theoretical analyses on an associative memory operation that uses a virtual oscillator network based on a spin-torque oscillator. The virtual network combines the concept of coupled oscillators with that of feedforward neural networks. Numerical experiments demonstrate successful associations of 60-pixel patterns with various memorized patterns. Moreover, the origin of the associative memory is shown to be forced synchronization driven by feedforward input, where phase differences among oscillators are fixed and correspond to the colors of the pixels in the pattern.

Nematronics: Reciprocal Coupling between Ionic Currents and Nematic Dynamics

Adopting a spintronics-inspired approach, we study the reciprocal coupling between ionic charge currents and nematic texture dynamics in a uniaxial nematic electrolyte. Assuming quenched fluid dynamics, we develop equations of motion analogously to spin torque and spin pumping. Based on the principle of least dissipation of energy, we derive the adiabatic "nematic torque" exerted by ionic currents on the nematic director field as well as the reciprocal motive force on ions due to the orientational dynamics of the director. We discuss several simple examples that illustrate the potential functionality of this coupling. Furthermore, using our phenomenological framework, we propose a practical means to extract the coupling strength through impedance measurements on a nematic cell. Exploring further applications based on this physics could foster the development of nematronics-nematic iontronics.

Hybrid spin Hall nano-oscillators based on ferromagnetic metal/ferrimagnetic insulator heterostructures

Spin-Hall nano-oscillators (SHNOs) are promising spintronic devices to realize current controlled GHz frequency signals in nanoscale devices for neuromorphic computing and creating Ising systems. However, traditional SHNOs devices based on transition metals have high auto-oscillation threshold currents as well as low quality factors and output powers. Here we demonstrate a new type of hybrid SHNO based on a permalloy (Py) ferromagnetic-metal nanowire and low-damping ferrimagnetic insulator, in the form of epitaxial lithium aluminum ferrite (LAFO) thin films. The superior characteristics of such SHNOs are associated with the excitation of larger spin-precession angles and volumes. We further find that the presence of the ferrimagnetic insulator enhances the auto-oscillation amplitude of spin-wave edge modes, consistent with our micromagnetic modeling. This hybrid SHNO expands spintronic applications, including providing new means of coupling multiple SHNOs for neuromorphic computing and advancing magnonics.

Enhanced spin-orbit torque and field-free switching in Au/TMDs/Ni hybrid structures

Spin-orbit torque (SOT) plays a significant role in spintronic logic and memory devices. However, due to the limited spin Hall angle and SOT symmetry in a heavy-metal-ferromagnet bilayer, further improving SOT efficiency and all-electric magnetization manipulation remain a challenge. Here we report enhanced SOT efficiency and all-electric switching in Au based magnetic structures, by inserting two-dimensional transition metal dichalcogenides (2D TMDs) with large spin-orbit coupling. With the TMD spacer insert, both damping-like and field-like SOTs are improved, and an unconventional out-of-plane damping-like SOT is induced, due to the interface orbital hybridization, modified spin-mixing conductance and orbital current. Moreover, current induced field-free magnetization switching is demonstrated in Au/WTe₂/Ni and Au/MoS₂/Ni devices, and it shows multiple intermediate states and can be efficiently controlled by an electric current. Our results open a path for increasing torques and expand the application of 2D TMDs in spintronic devices for neuromorphic computing.

3D Interconnected Magnetic Nanowire Networks as Potential Integrated Multistate Memristors

Interconnected magnetic nanowire (NW) networks offer a promising platform for three-dimensional (3D) information storage and integrated neuromorphic computing. Here we report discrete propagation of magnetic states in interconnected Co nanowire networks driven by magnetic field and current, manifested in distinct magnetoresistance (MR) features. In these networks, when only a few interconnected NWs were measured, multiple MR kinks and local minima were observed, including a significant minimum at a positive field during the descending field sweep. Micromagnetic simulations showed that this unusual feature was due to domain wall (DW) pinning at the NW intersections, which was confirmed by off-axis electron holography imaging. In a complex network with many intersections, sequential switching of nanowire sections separated by interconnects was observed, along with stochastic characteristics. The pinning/depinning of the DWs can be further controlled by the driving current density. These results illustrate the promise of such interconnected networks as integrated multistate memristors.

Periodogram-Based Detection of Unknown Frequencies in Time-Resolved Scanning Transmission X-ray Microscopy

Pump-probe time-resolved imaging is a powerful technique that enables the investigation of dynamical processes. Signal-to-noise and sampling rate restrictions normally require that cycles of an excitation are repeated many times with the final signal reconstructed using a reference. However, this approach imposes restrictions on the types of dynamical processes that can be measured, namely, that they are phase locked to a known external signal (e.g., a driven oscillation or impulse). This rules out many interesting processes such as auto-oscillations and spontaneously forming populations, e.g., condensates. In this work we present a method for time-resolved imaging, based on the Schuster periodogram, that allows for the reconstruction of dynamical processes where the intrinsic frequency is not known. In our case we use time of arrival detection of X-ray photons to reconstruct magnetic dynamics without using a priori information on the dynamical frequency. This proof-of-principle demonstration will allow for the extension of pump-probe time-resolved imaging to the important class of processes where the dynamics are not locked to a known external signal and in its presented formulation can be readily adopted for X-ray imaging and also adapted for wider use.

Structural plasticity driven by task performance leads to criticality signatures in neuromorphic oscillator networks

Oscillator networks rapidly become one of the promising vehicles for energy-efficient computing due to their intrinsic parallelism of execution. The criticality property of the oscillator-based networks is regarded to be essential for performing complex tasks. There are numerous bio-inspired synaptic and structural plasticity mechanisms available, especially for spiking neural networks, which can drive the network towards the criticality. However, there is no solid connection between these self-adaption mechanisms and the task performance, and it is not clear how and why particular self-adaptation mechanisms contribute to the solution of the task, although their relation to criticality is understood. Here we propose an evolutionary approach for the structural plasticity that relies solely on the task performance and does not contain any task-independent adaptation mechanisms, which usually contribute towards the criticality of the network. As a driver for the structural plasticity, we use a direct binary search guided by the performance of the classification task that can be interpreted as an interaction of the network with the environment. Remarkably, such interaction with the environment brings the network to criticality, although this property was not a part of the objectives of the employed structural plasticity mechanism. This observation confirms a duality of criticality and task performance, and legitimizes internal activity-dependent plasticity mechanisms from the viewpoint of evolution as mechanisms contributing to the task performance, but following the dual route. Finally, we analyze the trained network against task-independent information-theoretic measures and identify the interconnection graph’s entropy to be an essential ingredient for the classification task performance and network’s criticality.

Quantifying the computational capability of a nanomagnetic reservoir computing platform with emergent magnetisation dynamics

Devices based on arrays of interconnected magnetic nano-rings with emergent magnetization dynamics have recently been proposed for use in reservoir computing applications, but for them to be computationally useful it must be possible to optimise their dynamical responses. Here, we use a phenomenological model to demonstrate that such reservoirs can be optimised for classification tasks by tuning hyperparameters that control the scaling and input-rate of data into the system using rotating magnetic fields. We use task-independent metrics to assess the rings' computational capabilities at each set of these hyperparameters and show how these metrics correlate directly to performance in spoken and written digit recognition tasks. We then show that these metrics, and performance in tasks, can be further improved by expanding the reservoir's output to include multiple, concurrent measures of the ring arrays' magnetic states.

Spin-Wave Channeling in Magnetization-Graded Nanostrips

Magnetization-graded ferromagnetic nanostrips are proposed as potential prospects to channel spin waves. Here, a controlled reduction of the saturation magnetization enables the localization of the propagating magnetic excitations in the same way that light is controlled in an optical fiber with a varying refraction index. The theoretical approach is based on the dynamic matrix method, where the magnetic nanostrip is divided into small sub-strips. The dipolar and exchange interactions between sub-strips have been considered to reproduce the spin-wave dynamics of the magnonic fiber. The transition from one strip to an infinite thin film is presented for the Damon-Eshbach geometry, where the nature of the spin-wave modes is discussed. An in-depth analysis of the spin-wave transport as a function of the saturation magnetization profile is provided. It is predicted that it is feasible to induce a remarkable channeling of the spin waves along the zones with a reduced saturation magnetization, even when such a reduction is tiny. The results are compared with micromagnetic simulations, where a good agreement is observed between both methods. The findings have relevance for envisioned future spin-wave-based magnonic devices operating at the nanometer scale.

Dual-axis control of magnetic anisotropy in a single crystal Co2MnSi thin film through piezo-voltage-induced strain

Voltage controlled magnetic anisotropy (VCMA) has been considered as an effective method in traditional magnetic devices with lower power consumption. In this article, we have investigated the dual-axis control of magnetic anisotropy in Co₂MnSi/GaAs/PZT hybrid heterostructures through piezo-voltage-induced strain using longitudinal magneto-optical Kerr effect (LMOKE) microscopy. The major modification of in-plane magnetic anisotropy of the Co₂MnSi thin film is controlled obviously by the piezo-voltages of the lead zirconate titanate (PZT) piezotransducer, accompanied by the coercivity field and magnetocrystalline anisotropy significantly manipulated. Because in-plane cubic magnetic anisotropy and uniaxial magnetic anisotropy coexist in the Co₂MnSi thin film, the initial double easy axes of cubic split to an easiest axis (square loop) and an easier axis (two-step loop). While the stress direction is parallel to the [1-10] easiest axis (sample I), the square loop of the [1-10] direction could transform to a two-step loop under the negative piezo-voltages (compressed state). At the same time, the initial two-step loop of the [110] axis simultaneously changes to a square loop (the easiest axis). Otherwise, we designed and fabricated the sample II in which the PZT stress is parallel to the [110] two-step axis. The phenomenon of VCMA was also obtained along the [110] and [1-10] directions. However, the manipulated results of sample II were in contrast to those of the sample I under the piezo-voltages. Thus, an effective dual-axis regulation of the in-plane magnetization rotation was demonstrated in this work. Such a finding proposes a more optimized method for the magnetic logic gates and memories based on voltage-controlled magnetic anisotropy in the future.

MgO Heterostructures: From Synthesis to Applications

The energy storage capacity of batteries and supercapacitors has seen rising demand and problems as large-scale energy storage systems and electric gadgets have become more widely adopted. With the development of nano-scale materials, the electrodes of these devices have changed dramatically. Heterostructure materials have gained increased interest as next-generation materials due to their unique interfaces, resilient structures and synergistic effects, providing the capacity to improve energy/power outputs and battery longevity. This review focuses on the role of MgO in heterostructured magnetic and energy storage devices and their applications and synthetic strategies. The role of metal oxides in manufacturing heterostructures has received much attention, especially MgO. Heterostructures have stronger interactions between tightly packed interfaces and perform better than single structures. Due to their typical physical and chemical properties, MgO heterostructures have made a breakthrough in energy storage. In perpendicularly magnetized heterostructures, the MgO's thickness significantly affects the magnetic properties, which is good news for the next generation of high-speed magnetic storage devices.

Voltage-driven gigahertz frequency tuning of spin Hall nano-oscillators

Spin Hall nano-oscillators (SHNOs) exploiting current-driven magnetization auto-oscillation have recently received much attention because of their potential for neuromorphic computing. Widespread applications of neuromorphic devices with SHNOs require an energy-efficient method of tuning oscillation frequency over broad ranges and storing trained frequencies in SHNOs without the need for additional memory circuitry. While the voltage-driven frequency tuning of SHNOs has been demonstrated, it was volatile and limited to megahertz ranges. Here, we show that the frequency of SHNOs is controlled up to 2.1 GHz by an electric field of 1.25 MV/cm. The large frequency tuning is attributed to the voltage-controlled magnetic anisotropy (VCMA) in a perpendicularly magnetized Ta/Pt/[Co/Ni]_n/Co/AlO_x structure. Moreover, the non-volatile VCMA effect enables cumulative control of the frequency using repetitive voltage pulses which mimic the potentiation and depression functions of biological synapses. Our results suggest that the voltage-driven frequency tuning of SHNOs facilitates the development of energy-efficient neuromorphic devices.

Optical and optoelectronic neuromorphic devices based on emerging memory technologies

As artificial intelligence continues its rapid development, inevitable challenges arise for the mainstream computing hardware to process voluminous data (Big data). The conventional computer system based on von Neumann architecture with separated processor unit and memory is approaching the limit of computational speed and energy efficiency. Thus, novel computing architectures such as in-memory computing and neuromorphic computing based on emerging memory technologies have been proposed. In recent years, light is incorporated into computational devices, beyond the data transmission in traditional optical communications, due to its innate superiority in speed, bandwidth, energy efficiency, etc. Thereinto, photo-assisted and photoelectrical synapses are developed for neuromorphic computing. Additionally, both the storage and readout processes can be implemented in optical domain in some emerging photonic devices to leverage unique properties of photonics. In this review, we introduce typical photonic neuromorphic devices rooted from emerging memory technologies together with corresponding operational mechanisms. In the end, the advantages and limitations of these devices originated from different modulation means are listed and discussed.

Picosecond optospintronic tunnel junctions

Spintronic devices have become promising candidates for next-generation memory architecture. However, state-of-the-art devices, such as perpendicular magnetic tunnel junctions (MTJs), are still fundamentally constrained by a subnanosecond speed limitation, which has remained a long-lasting scientific obstacle in the ultrafast spintronics field. The highlight of our work is the demonstration of an optospintronic tunnel junction, an all-optical MTJ device which emerges as a new category of integrated photonic–spintronic memory. We demonstrate 1) laser-induced deterministic and efficient writing by an all-optical approach and electrical readout by tunnel magnetoresistance, 2) writing speed within 10 ps, demonstrated by femtosecond-resolved measurements, and 3) integration with state-of-the-art MTJ performance and a complementary metal–oxide–semiconductor-compatible fabrication progress.

Perpendicular magnetic tunnel junctions (p-MTJs), as building blocks of spintronic devices, offer substantial potential for next-generation nonvolatile memory applications. However, their performance is fundamentally hindered by a subnanosecond speed limitation, due to spin-polarized-current-based mechanisms. Here, we report an optospintronic tunnel junction (OTJ) device with a picosecond switching speed, ultralow power, high magnetoresistance ratio, high thermal stability, and nonvolatility. This device incorporates an all-optically switchable Gd/Co bilayer coupled to a CoFeB/MgO-based p-MTJ, by subtle tuning of Ruderman–Kittel–Kasuya–Yosida interaction. An all-optical “writing” of the OTJ within 10 ps is experimentally demonstrated by time-resolved measurements. The device shows a reliable resistance “readout” with a relatively high tunnel magnetoresistance of 34.7%, as well as promising scaling toward the nanoscale with ultralow power consumption (<100 fJ for a 50-nm-sized bit). Our proof-of-concept demonstration of OTJ might ultimately pave the way toward a new category of integrated spintronic–photonic memory devices.

Significant Reorientation Transition of Magnetic Damping Anisotropy in Co2FeAl Heusler Alloy Films at Low Temperatures

The temperature (T) dependences of magnetization dynamics, especially for magnetic damping anisotropy, have been systematically investigated in well-ordered Co2FeAl films with a biaxial anisotropy. It is found that the damping anisotropy factor Q, defined as the fractional difference of damping between the hard and easy axes, changes from 0.35 to -0.09 as T decreases from 300 to 80 K, performing a distinctive reorientation transition at T ∼ 200 K. Through the thickness-dependent damping measurement results, the damping anisotropy reorientation is verified to originate from the competitions between the intrinsic anisotropic distribution of bulk spin orbit coupling and the interfacial two-magnon scattering. The former governs the effective damping at high temperatures, while the latter with an opposite fourfold symmetry gradually plays a dominant role at reduced temperatures, leading to the transition of the Q value from positive to negative. The clear clarification of damping anisotropy variation as well as the underlying mechanism in this study would be of great importance for designing key spintronic devices with optimized dynamic magnetic properties.

Freezing and thawing magnetic droplet solitons

Magnetic droplets are non-topological magnetodynamical solitons displaying a wide range of complex dynamic phenomena with potential for microwave signal generation. Bubbles, on the other hand, are internally static cylindrical magnetic domains, stabilized by external fields and magnetostatic interactions. In its original theory, the droplet was described as an imminently collapsing bubble stabilized by spin transfer torque and, in its zero-frequency limit, as equivalent to a bubble. Without nanoscale lateral confinement, pinning, or an external applied field, such a nanobubble is unstable, and should collapse. Here, we show that we can freeze dynamic droplets into static nanobubbles by decreasing the magnetic field. While the bubble has virtually the same resistance as the droplet, all signs of low-frequency microwave noise disappear. The transition is fully reversible and the bubble can be thawed back into a droplet if the magnetic field is increased under current. Whereas the droplet collapses without a sustaining current, the bubble is highly stable and remains intact for days without external drive. Electrical measurements are complemented by direct observation using scanning transmission x-ray microscopy, which corroborates the analysis and confirms that the bubble is stabilized by pinning.

Magnetic droplets are a type of non-topological magnetic soliton, which are stabilised and sustained by spin-transfer torques for instance. Without this, they would collapse. Here Ahlberg et al show that by decreasing the applied magnetic field, droplets can be frozen, forming a static nanobubble

Transmission Electron Microscopy Study on the Effect of Thermal and Electrical Stimuli on Ge2Te3 Based Memristor Devices

Memristor devices fabricated using the chalcogenide Ge2Te3 phase change thin films in a metal-insulator-metal structure are characterized using thermal and electrical stimuli in this study. Once the thermal and electrical stimuli are applied, cross-sectional transmission electron microscopy (TEM) and X-ray energy-dispersive spectroscopy (XEDS) analyses are performed to determine structural and compositional changes in the devices. Electrical measurements on these devices showed a need for increasing compliance current between cycles to initiate switching from low resistance state (LRS) to high resistance state (HRS). The measured resistance in HRS also exhibited a steady decrease with increase in the compliance current. High resolution TEM studies on devices in HRS showed the presence of residual crystalline phase at the top-electrode/dielectric interface, which may explain the observed dependence on compliance current. XEDS study revealed diffusion related processes at dielectric-electrode interface characterized, by the separation of Ge2Te3 into Ge- and Te- enriched interfacial layers. This was also accompanied by spikes in O level at these regions. Furthermore, in-situ heating experiments on as-grown thin films revealed a deleterious effect of Ti adhesive layer, wherein the in-diffusion of Ti leads to further degradation of the dielectric layer. This experimental physics-based study shows that the large HRS/LRS ratio below the current compliance limit of 1 mA and the ability to control the HRS and LRS by varying the compliance current are attractive for memristor and neuromorphic computing applications.

Pure voltage-driven spintronic neuron based on stochastic magnetization switching behaviour

Voltage-driven stochastic magnetization switching in a nanomagnet has attracted more attention recently with its superiority in achieving energy-efficient artificial neuron. Here, a novel pure voltage-driven scheme with ∼27.66 aJ energy dissipation is proposed, which could rotate magnetization vector randomly using only a pair of electrodes covered on the multiferroic nanomagnet. Results show that the probability of 180° magnetization switching is examined as a sigmoid-like function of the voltage pulse width and magnitude, which can be utilized as the activation function of designed neuron. Considering the size errors of designed neuron in fabrication, it's found that reasonable thickness and width variations cause little effect on recognition accuracy for MNIST hand-written dataset. In other words, the designed pure voltage-driven spintronic neuron could tolerate size errors. These results open a new way toward the realization of artificial neural network with low power consumption and high reliability.

Visualizing the strongly reshaped skyrmion Hall effect in multilayer wire devices

Magnetic skyrmions are nanoscale spin textures touted as next-generation computing elements. When subjected to lateral currents, skyrmions move at considerable speeds. Their topological charge results in an additional transverse deflection known as the skyrmion Hall effect (SkHE). While promising, their dynamic phenomenology with current, skyrmion size, geometric effects and disorder remain to be established. Here we report on the ensemble dynamics of individual skyrmions forming dense arrays in Pt/Co/MgO wires by examining over 20,000 instances of motion across currents and fields. The skyrmion speed reaches 24 m/s in the plastic flow regime and is surprisingly robust to positional and size variations. Meanwhile, the SkHE saturates at ∼22^∘, is substantially reshaped by the wire edge, and crucially increases weakly with skyrmion size. Particle model simulations suggest that the SkHE size dependence — contrary to analytical predictions — arises from the interplay of intrinsic and pinning-driven effects. These results establish a robust framework to harness SkHE and achieve high-throughput skyrmion motion in wire devices.

Skyrmions - nanoscale, topological spin textures - are promising elements for next-generation computing due to their efficient coupling to currents in racetrack devices. Here, Tan et al. examine over 20,000 instances of current induced skyrmion motion to unveil a comprehensive picture of skyrmion dynamics across currents and fields.

Controllable magnetization precession dynamics and damping anisotropy in Co2FeAl Heusler-alloy films

Magnetization dynamics of the epitaxially-grown Co₂FeAl (CFA) thin films have been systematically investigated by the time-resolved magneto-optical Kerr effect (TR-MOKE). The dependences of precession frequency f, relaxation time τ and magnetic damping factor α upon the orientation of applied magnetic field are found to have a strong four-fold symmetry. Two series of samples with various substrate temperatures (T_s) and thickness (t_CFA) were prepared and a large Gilbert damping difference between the hard and easy axes is extracted to be 3.3 × 10^-3 after subtracting the extrinsic contributions of spin pumping, two-magnon scattering and magnetic inhomogeneities. The four-fold variation of Gilbert damping relates closely to the in-plane magnetocrystalline anisotropy and can be attributed to the anisotropic distribution of spin-orbit coupling. Our findings provide new insights into the anisotropic properties of magnetization and damping, which is very helpful for designing and optimizing advanced spintronic devices on different demands.

Electrically connected spin-torque oscillators array for 2.4 GHz WiFi band transmission and energy harvesting

The mutual synchronization of spin-torque oscillators (STOs) is critical for communication, energy harvesting and neuromorphic applications. Short range magnetic coupling-based synchronization has spatial restrictions (few µm), whereas the long-range electrical synchronization using vortex STOs has limited frequency responses in hundreds MHz (<500 MHz), restricting them for on-chip GHz-range applications. Here, we demonstrate electrical synchronization of four non-vortex uniformly-magnetized STOs using a single common current source in both parallel and series configurations at 2.4 GHz band, resolving the frequency-area quandary for designing STO based on-chip communication systems. Under injection locking, synchronized STOs demonstrate an excellent time-domain stability and substantially improved phase noise performance. By integrating the electrically connected eight STOs, we demonstrate the battery-free energy-harvesting system by utilizing the wireless radio-frequency energy to power electronic devices such as LEDs. Our results highlight the significance of electrical topology (series vs. parallel) while designing an on-chip STOs system.

Control of Structural and Magnetic Properties of Polycrystalline Co2FeGe Films via Deposition and Annealing Temperatures

Thin polycrystalline Co₂FeGe films with composition close to stoichiometry have been fabricated using magnetron co-sputtering technique. Effects of substrate temperature (T_S) and post-deposition annealing (T_a) on structure, static and dynamic magnetic properties were systematically studied. It is shown that elevated T_S (T_a) promote formation of ordered L2₁ crystal structure. Variation of T_S (T_a) allow modification of magnetic properties in a broad range. Saturation magnetization ~920 emu/cm³ and low magnetization damping parameter α ~ 0.004 were achieved for T_S = 573 K. This in combination with soft ferromagnetic properties (coercivity below 6 Oe) makes the films attractive candidates for spin-transfer torque and magnonic devices.

Spin-Torque Memristors Based on Perpendicular Magnetic Tunnel Junctions for Neuromorphic Computing

Spin-torque memristors are proposed in 2009, and can provide fast, low-power, and infinite memristive behavior for neuromorphic computing and large-density non-volatile memory. However, the strict requirements of combining high magnetoresistance, stable domain wall pinning and current-induced switching in a single device pose difficulties in physical implementation. Here, a nanoscale spin-torque memristor based on a perpendicular-anisotropy magnetic tunnel junction with a CoFeB/W/CoFeB composite free layer structure is experimentally demonstrated. Its tunneling magnetoresistance is higher than 200%, and memristive behavior can be realized by spin-transfer torque switching. Memristive states are retained by strong domain wall pinning effects in the free layer. Experiments and simulations suggest that nanoscale vertical chiral spin textures can form around clusters of W atoms under the combined effect of opposite Dzyaloshinskii-Moriya interactions and the Ruderman-Kittel-Kasuya-Yosida interaction between the two CoFeB free layers. Energy fluctuation caused by these textures may be the main reason for the strong pinning effect. With the experimentally demonstrated memristive behavior and spike-timing-dependent plasticity, a spiking neural network to perform handwritten pattern recognition in an unsupervised manner is simulated. Due to advantages such as long endurance and high speed, the spin-torque memristors are competitive in the future applications for neuromorphic computing.

Magnonic Bending, Phase Shifting and Interferometry in a 2D Reconfigurable Nanodisk Crystal

Strongly interacting nanomagnetic systems are pivotal across next-generation technologies including reconfigurable magnonics and neuromorphic computation. Controlling magnetization states and local coupling between neighboring nanoelements allows vast reconfigurability and a host of associated functionalities. However, existing designs typically suffer from an inability to tailor interelement coupling post-fabrication and nanoelements restricted to a pair of Ising-like magnetization states. Here, we propose a class of reconfigurable magnonic crystals incorporating nanodisks as the functional element. Ferromagnetic nanodisks are crucially bistable in macrospin and vortex states, allowing interelement coupling to be selectively activated (macrospin) or deactivated (vortex). Through microstate engineering, we leverage the distinct coupling behaviors and magnonic band structures of bistable nanodisks to achieve reprogrammable magnonic waveguiding, bending, gating, and phase-shifting across a 2D network. The potential of nanodisk-based magnonics for wave-based computation is demonstrated via an all-magnon interferometer exhibiting XNOR logic functionality. Local microstate control is achieved here via topological magnetic writing using a magnetic force microscope tip.

Competing memristors for brain-inspired computing

The expeditious development of information technology has led to the rise of artificial intelligence (AI). However, conventional computing systems are prone to volatility, high power consumption, and even delay between the processor and memory, which is referred to as the von Neumann bottleneck, in implementing AI. To address these issues, memristor-based neuromorphic computing systems inspired by the human brain have been proposed. A memristor can store numerous values by changing its resistance and emulate artificial synapses in brain-inspired computing. Here, we introduce six types of memristors classified according to their operation mechanisms: ionic migration, phase change, spin, ferroelectricity, intercalation, and ionic gating. We review how memristor-based neuromorphic computing can learn, infer, and even create, using various artificial neural networks. Finally, the challenges and perspectives in the competing memristor technology for neuromorphic computing systems are discussed.

Roadmap of spin-orbit torques

Spin-orbit torque (SOT) is an emerging technology that enables the efficient manipulation of spintronic devices. The initial processes of interest in SOTs involved electric fields, spin-orbit coupling, conduction electron spins and magnetization. More recently interest has grown to include a variety of other processes that include phonons, magnons, or heat. Over the past decade, many materials have been explored to achieve a larger SOT efficiency. Recently, holistic design to maximize the performance of SOT devices has extended material research from a nonmagnetic layer to a magnetic layer. The rapid development of SOT has spurred a variety of SOT-based applications. In this Roadmap paper, we first review the theories of SOTs by introducing the various mechanisms thought to generate or control SOTs, such as the spin Hall effect, the Rashba-Edelstein effect, the orbital Hall effect, thermal gradients, magnons, and strain effects. Then, we discuss the materials that enable these effects, including metals, metallic alloys, topological insulators, two-dimensional materials, and complex oxides. We also discuss the important roles in SOT devices of different types of magnetic layers, such as magnetic insulators, antiferromagnets, and ferrimagnets. Afterward, we discuss device applications utilizing SOTs. We discuss and compare three-terminal and two-terminal SOT-magnetoresistive random-access memories (MRAMs); we mention various schemes to eliminate the need for an external field. We provide technological application considerations for SOT-MRAM and give perspectives on SOT-based neuromorphic devices and circuits. In addition to SOT-MRAM, we present SOT-based spintronic terahertz generators, nano-oscillators, and domain wall and skyrmion racetrack memories. This paper aims to achieve a comprehensive review of SOT theory, materials, and applications, guiding future SOT development in both the academic and industrial sectors.

Spin hall nano-oscillators based on two-dimensional Fe3GeTe2 magnetic materials

Two-dimensional (2D) magnetic materials with high perpendicular anisotropy, such as Fe₃GeTe₂, have the potential to build spintronic devices with better performance and lower power consumption. Here, we examine microwave emissions in Fe₃GeTe₂/Pt spin Hall nano-oscillators with different numbers of layers of Fe₃GeTe₂ using micromagnetic simulations. We predict that auto-oscillation with a frequency of >30 GHz can be driven by spin-orbit torque (SOT) and the frequency is tunable with current. Observing the dynamic behaviors of magnetization dynamic reveals that non-localized spin-wave propagates in Fe₃GeTe₂ with a spatially varied wavelength due to Joule heat and forms certain special bubble-like magnetic structure. Our results indicate SHNOs comprising a 2D magnetic material has the potential to develop future spintronic oscillator with low power consumption and high performance.

Room-Temperature Manipulation of Magnetization Angle, Achieved with an All-Solid-State Redox Device

An all-solid-state redox device, composed of magnetite (Fe₃O₄) thin film and Li⁺ conducting electrolyte thin film, was fabricated for the manipulation of a magnetization angle at room temperature (RT). This is a key technology for the creation of efficient spintronics devices, but has not yet been achieved at RT by other carrier doping methods. Variations in magnetization angle and magnetic stability were precisely tracked through the use of planar Hall measurements at RT. The magnetization angle was reversibly manipulated at 10° by maintaining magnetic stability. Meanwhile, the manipulatable angle reached 56°, although the manipulation became irreversible when the magnetic stability was reduced. This large manipulation of magnetic angle was achieved through tuning of the 3d electron number and modulation of the internal strain in the Fe₃O₄ due to the insertion of high-density Li⁺ (approximately 10²¹ cm^-3). This RT manipulation is applicable to highly integrated spintronics devices due to its simple structure and low electric power consumption.

Element-Specific Detection of Sub-Nanosecond Spin-Transfer Torque in a Nanomagnet Ensemble

Spin currents can exert spin-transfer torques on magnetic systems even in the limit of vanishingly small net magnetization, as recently shown for antiferromagnets. Here, we experimentally show that a spin-transfer torque is operative in a macroscopic ensemble of weakly interacting, randomly magnetized Co nanomagnets. We employ element- and time-resolved X-ray ferromagnetic resonance (XFMR) spectroscopy to directly detect subnanosecond dynamics of the Co nanomagnets, excited into precession with cone angle ≳0.003° by an oscillating spin current. XFMR measurements reveal that as the net moment of the ensemble decreases, the strength of the spin-transfer torque increases relative to those of magnetic field torques. Our findings point to spin-transfer torque as an effective way to manipulate the state of nanomagnet ensembles at subnanosecond time scales.

Implementing an Insect Brain Computational Circuit Using III-V Nanowire Components in a Single Shared Waveguide Optical Network

Recent developments in photonics include efficient nanoscale optoelectronic components and novel methods for subwavelength light manipulation. Here, we explore the potential offered by such devices as a substrate for neuromorphic computing. We propose an artificial neural network in which the weighted connectivity between nodes is achieved by emitting and receiving overlapping light signals inside a shared quasi 2D waveguide. This decreases the circuit footprint by at least an order of magnitude compared to existing optical solutions. The reception, evaluation, and emission of the optical signals are performed by neuron-like nodes constructed from known, highly efficient III-V nanowire optoelectronics. This minimizes power consumption of the network. To demonstrate the concept, we build a computational model based on an anatomically correct, functioning model of the central-complex navigation circuit of the insect brain. We simulate in detail the optical and electronic parts required to reproduce the connectivity of the central part of this network using previously experimentally derived parameters. The results are used as input in the full model, and we demonstrate that the functionality is preserved. Our approach points to a general method for drastically reducing the footprint and improving power efficiency of optoelectronic neural networks, leveraging the superior speed and energy efficiency of light as a carrier of information.

Nonvolatile Multistates Memories for High-Density Data Storage

In the current information age, the realization of memory devices with energy efficient design, high storage density, nonvolatility, fast access, and low cost is still a great challenge. As a promising technology to meet these stringent requirements, nonvolatile multistates memory (NMSM) has attracted lots of attention over the past years. Owing to the capability to store data in more than a single bit (0 or 1), the storage density is dramatically enhanced without scaling down the memory cell, making memory devices more efficient and less expensive. Multistates in a single cell also provide an unconventional in-memory computing platform beyond the Von Neumann architecture and enable neuromorphic computing with low power consumption. In this review, an in-depth perspective is presented on the recent progress and challenges on the device architectures, material innovation, working mechanisms of various types of NMSMs, including flash, magnetic random-access memory (MRAM), resistive random-access memory (RRAM), ferroelectric random-access memory (FeRAM), and phase-change memory (PCM). The intriguing properties and performance of these NMSMs, which are the key to realizing highly integrated memory hierarchy, are discussed and compared.

Robust phase shift keying modulation method for spin torque nano-oscillator

The spin torque nano-oscillator (STNO) is a very promising candidate for next generation telecommunication systems due to its small size ~100 nm and high output frequency range. However, it still suffers low output power, usually smaller than µW, and very high phase noise. Also, the modulation method for the STNO should be further developed. The frequency modulation and amplitude modulation method for STNO can be easily applied because of the non-linear nature of STNO, yet it is very rare to see the proposal of a phase modulation method. In this work, we propose a robust phase shift keying modulation method for STNO. Its feasibility is demonstrated with both theoretical and numerical analysis, and its robustness is investigated under room temperature thermal noise. It is shown that our proposed phase modulation method can tune the phase arbitrarily, while the modulation speed can be as fast as 10 ns at room temperature. Comparing with the other phase modulation method, our approach has advantages of larger phase tuning range and stronger robustness against thermal noise.

A New Approach to the Fabrication of Memristive Neuromorphic Devices: Compositionally Graded Films

Energy-efficient computing paradigms beyond conventional von-Neumann architecture, such as neuromorphic computing, require novel devices that enable information storage at nanoscale in an analogue way and in-memory computing. Memristive devices with long-/short-term synaptic plasticity are expected to provide a more capable neuromorphic system compared to traditional Si-based complementary metal-oxide-semiconductor circuits. Here, compositionally graded oxide films of Al-doped Mg_xZn_1−xO (g-Al:MgZnO) are studied to fabricate a memristive device, in which the composition of the film changes continuously through the film thickness. Compositional grading in the films should give rise to asymmetry of Schottky barrier heights at the film-electrode interfaces. The g-Al:MgZnO films are grown by using aerosol-assisted chemical vapor deposition. The current-voltage (I-V) and capacitance-voltage (C-V) characteristics of the films show self-rectifying memristive behaviors which are dependent on maximum applied voltage and repeated application of electrical pulses. Endurance and retention performance tests of the device show stable bipolar resistance switching (BRS) with a short-term memory effect. The short-term memory effects are ascribed to the thermally activated release of the trapped electrons near/at the g-Al:MgZnO film-electrode interface of the device. The volatile resistive switching can be used as a potential selector device in a crossbar memory array and a short-term synapse in neuromorphic computing.

Influence of flicker noise and nonlinearity on the frequency spectrum of spin torque nano-oscillators

The correlation of phase fluctuations in any type of oscillator fundamentally defines its spectral shape. However, in nonlinear oscillators, such as spin torque nano-oscillators, the frequency spectrum can become particularly complex. This is specifically true when not only considering thermal but also colored 1/f flicker noise processes, which are crucial in the context of the oscillator’s long term stability. In this study, we address the frequency spectrum of spin torque oscillators in the regime of large-amplitude steady oscillations experimentally and as well theoretically. We particularly take both thermal and flicker noise into account. We perform a series of measurements of the phase noise and the spectrum on spin torque vortex oscillators, notably varying the measurement time duration. Furthermore, we develop the modelling of thermal and flicker noise in Thiele equation based simulations. We also derive the complete phase variance in the framework of the nonlinear auto-oscillator theory and deduce the actual frequency spectrum. We investigate its dependence on the measurement time duration and compare with the experimental results. Long term stability is important in several of the recent applicative developments of spin torque oscillators. This study brings some insights on how to better address this issue.

Digital and analogue modulation and demodulation scheme using vortex-based spin torque nano-oscillators

In conventional communications systems, information is transmitted by modulating the frequency, amplitude or phase of the carrier signal, which often occurs in a binary fashion over a very narrow bandwidth. Recently, ultra-wideband signal transmission has gained interest for local communications in technologies such as autonomous local sensor networks and on-chip communications, which presents a challenge for conventional electronics. Spin-torque nano-oscillators (STNOs) have been studied as a potentially low power highly tunable frequency source, and in this report we expand on this to show how a specific dynamic phase present in vortex-based STNOs makes them also well suited as Wideband Analogue Dynamic Sensors (WADS). This multi-functionality of the STNOs is the basis of a new modulation and demodulation scheme, where nominally identical devices can be used to transmit information in both a digital or analogue manner, with the potential to allow the highly efficient transmittance of data.

Demonstration of a pseudo-magnetization based simultaneous write and read operation in a Co60Fe20B20/Pb(Mg1/3Nb2/3)0.7Ti0.3O3 heterostructure

Taking advantage of the magnetoelectric and its inverse effect, this article demonstrates strain-mediated magnetoelectric write and read operations simultaneously in Co60Fe20B20/Pb(Mg1/3Nb2/3)0.7Ti0.3O3 heterostructures based on a pseudo-magnetization µ ≡ mx2 - my2. By applying an external DC-voltage across a (011)-cut PMN-PT substrate, the ferroelectric polarization is re-oriented, which results in an anisotropic in-plane strain that transfers to the CoFeB thin film and changes its magnetic anisotropy Hk. The change in Hk in-turn results in a 90° rotation of the magnetic easy axis for sufficiently high voltages. Simultaneously, the inverse effect is employed to read changes of the magnetic properties. The change of magnetization in ferromagnetic (FM) layer induces an elastic stress in the piezoelectric (PE) layer, which generates a PE potential that can be used to readout the magnetic state of the FM layer. The experimental results are in excellent qualitative agreement with an equivalent circuit model that considers how magnetic properties are electrically controlled in such a PE/FM heterostructure and how a back-voltage is generated due to changing magnetic properties in a self-consistent model. We demonstrated that a change of easy axis of magnetization due to an applied voltage can be directly used for information processing, which is essential for future ME based devices.